StanCon 2018
who it's for
applied Bayesian modelers, statistical programmers, biostatisticians, time series analysts, computational statisticians, psychometricians
topics
joint longitudinal and survival models; Bayesian disease progression models; Scala DSL that emits Stan; hidden Markov models in Stan; Prophet forecasting with changepoints; ICAR areal spatial smoothing; blockless Stan compiler and elaboration; variational Bayes for hierarchical IRT; nonlinear algebraic solver with implicit Jacobian; regularized horseshoe for high-dimensional regression; embedded eigenvalue solvers for PDE inversion
| title | author | length |
|---|---|---|
| SamBrillman | SamBrillman | 20m |
Joint shared-parameter models for multiple longitudinal biomarkers and time-to-event data get implemented in rstanarm stan_jm and fit via Stan, handling… | ||
| Arya | Arya | 19m |
A Bayesian generative disease‑progression model implemented in Stan uses a latent severity axis (age on x), four‑parameter logistic biomarker curves, I-splines… | ||
| JoeWingbermuehle | JoeWingbermuehle | 15m |
A Scala DSL generates Stan code and runs it, claiming a type-safe Stan DSL that maps Scala data to Stan types, surfaces errors in the IDE, and exports models… | ||
| MichaelWeylandt | MichaelWeylandt | 18m |
Asserts hidden Markov models are practical in Stan by implementing the calculable log-likelihood via the forward algorithm and sampling the posterior with… | ||
| SeanTaylorBenLetham | SeanTaylorBenLetham | 42m |
Facebook builds Prophet, a time‑series tool implemented in R and Python on Stan MCMC, that models real business series with piecewise linear trend and Fourier… | ||
| Mitzi | Mitzi | 27m |
Claims that the ICAR as improper prior with a sum-to-zero constraint gives fast, usable areal smoothing; implements the pairwise-difference formulation in Stan… | ||
| MariaGorinova | MariaGorinova | 22m |
Claims that Stan's block syntax is unnecessary and implements a prototype slick Stan compiler that shreds blockless programs back into Stan, demonstrating… | ||
| RobertKubinec | RobertKubinec | 18m |
Package ideal Stan implements hierarchical ideal‑point (IRT‑style) models for binary and ordinal data, built in Stan with variational Bayes and automatic… | ||
| CharlesMarg | CharlesMarg | 17m |
Describes a new Stan 2.17 feature: a Stan 2.17 nonlinear algebraic solver that finds steady states by root finding instead of long simulation and returns… | ||
| DanielLee720 | DanielLee720 | 17m |
About four years after version 1.0 the project shows 32 releases, roughly 1,500 citations and a manual that grows from 178→620 pages. It ships a custom math… | ||
| BenBales | BenBales | 21m |
Bayesian inversion recovers elastic constants of single‑crystal superalloys from resonance modes using Stan with embedded eigenvalue solvers and custom… | ||
| Aki720 | Aki720 | 25m |
Claims a concrete prior that outperforms Lasso on sparse high P low N regression, shows regularized horseshoe formulation that prevents complete separation in… | ||
| ManualRivas | ManualRivas | 42m |
Uses Stan and BRMS to fit mixture models to summary GWAS statistics from the UK Biobank (~500,000), estimating genetic correlation, scale and the fraction pi… | ||
| AkiTutorial | AkiTutorial | 01h 18m |
Covers concrete methods and failures: uses PSIS-LOO via the loo package, reports pareto k > 0.7 as a badness threshold and offers loo+ exact re-computation for… | ||
| SusanHolmes | SusanHolmes | 51m |
Claims a reproducible pipeline that quantifies uncertainty in manifold-style projections and rankings, using Bayesian uni-dimensional scaling with… | ||
| Camelia | Camelia | 20m |
A new threshold test claims to directly estimate search thresholds and risk distributions using a Bayesian hierarchical latent‑variable model applied to 4.5… | ||
| JimSavage | JimSavage | 19m |
Implements an aggregate random coefficients logit in Stan to handle only market-level shares while modeling individual heterogeneity with multivariate normal… | ||
| Constantine | Constantine | 18m |
Claims a Bayesian latent-variable model for mixed binary and continuous trial outcomes that combines effects into a single preference score using MCDA and… | ||
| Leah | Leah | 22m |
Implements the Bayesian g‑formula in Stan, fitting logistic outcome and mediator models and using posterior predictive draws in the generated quantities block… | ||
| Fausto | Fausto | 21m |
An archival-style recording labeled "Fausto" contains music and unintelligible Spanish captions but no technical content. It does not present technologies… | ||
| Andrew | Andrew | 36m |
Argues for practical Bayesian work by showing what was done: a hierarchical analysis of a sexual‑harassment survey with hundreds of thousands of respondents… | ||
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